class_docstr: Abstract clusterer which takes tokens and maps them into a vector space.
  Optionally performs singular value decomposition to reduce the
  dimensionality.
docstr: Returns the likelihood of the vector belonging to the cluster.
docstr_tok: ["Returns","the","likelihood","of","the","vector","belonging","to","the","cluster","."]
code: def likelihood_vectorspace(self, vector, cluster):
      """
      Returns the likelihood of the vector belonging to the cluster.
      """
      predicted = self.classify_vectorspace(vector)
      return 1.0 if cluster == predicted else 0.0
  
imports: import copy
  from abc import abstractmethod
  from math import sqrt
  from sys import stdout
  from nltk.cluster.api import ClusterI
label_desc: Use image node_id 7 for calling the VectorSpaceClusterer obj's underlying member method code with example usage: obj.likelihood_vectorspace(vector, cluster) and returns: unknown